Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "60" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460015 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.714381 | 14.784285 | -0.066192 | 11.637773 | 0.357222 | 6.951723 | 1.295929 | 3.193599 | 0.5957 | 0.0757 | 0.4681 | nan | nan |
| 2460014 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 1.011973 | 12.406899 | -0.218761 | 8.779668 | 0.087114 | 10.444884 | 1.327943 | 2.633047 | 0.5655 | 0.0532 | 0.4579 | nan | nan |
| 2460013 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.594073 | 14.804989 | -0.088219 | 11.618918 | 0.510901 | 6.975462 | 1.210040 | 3.717934 | 0.5906 | 0.0697 | 0.4724 | nan | nan |
| 2460012 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.407701 | 13.894298 | -0.242154 | 11.400661 | 0.754426 | 7.709722 | 4.307500 | 7.484120 | 0.5913 | 0.0733 | 0.4632 | nan | nan |
| 2460011 | RF_maintenance | 100.00% | 0.92% | 100.00% | 0.00% | - | - | 0.517455 | 14.891704 | -0.334255 | 15.257099 | 19.488829 | 15.857849 | 4.250996 | 3.397269 | 0.5832 | 0.0765 | 0.4786 | nan | nan |
| 2460010 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.986951 | 16.295916 | -0.519363 | 12.636289 | 0.053648 | 10.391835 | 0.858339 | 2.982025 | 0.6043 | 0.0760 | 0.5006 | nan | nan |
| 2460009 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.626717 | 15.015085 | -0.302631 | 13.908379 | 0.095143 | 8.777299 | 0.707976 | 3.292995 | 0.6063 | 0.0793 | 0.4941 | nan | nan |
| 2460008 | RF_maintenance | 100.00% | 0.00% | 91.73% | 0.00% | - | - | 0.014746 | 18.488821 | -1.203527 | 15.312180 | 2.564931 | 7.715746 | 0.893621 | 5.621983 | 0.6568 | 0.1086 | 0.5152 | nan | nan |
| 2460007 | RF_maintenance | 100.00% | 0.00% | 98.81% | 0.00% | - | - | 0.406703 | 13.817860 | -0.235116 | 11.975844 | 0.258377 | 7.168053 | 6.577181 | 3.394598 | 0.6174 | 0.0822 | 0.5008 | nan | nan |
| 2459999 | RF_maintenance | 0.00% | 89.14% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.1624 | 0.0365 | 0.1431 | nan | nan |
| 2459998 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.265232 | 11.648321 | -0.226664 | 10.136932 | 0.518058 | 10.162864 | 12.009825 | 3.230424 | 0.6116 | 0.0670 | 0.4960 | nan | nan |
| 2459997 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.294429 | 12.729802 | -0.284608 | 10.892749 | 0.241427 | 9.567914 | 14.120246 | 4.340825 | 0.6293 | 0.0751 | 0.5048 | nan | nan |
| 2459996 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.586292 | 13.701306 | 0.067738 | 13.329098 | 0.471000 | 9.207881 | 4.682389 | 1.908670 | 0.6333 | 0.0738 | 0.5076 | nan | nan |
| 2459995 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.470560 | 13.909784 | -0.420472 | 12.528205 | -0.002282 | 9.406282 | 5.557310 | 1.735604 | 0.6302 | 0.0798 | 0.4979 | nan | nan |
| 2459994 | RF_maintenance | 100.00% | 0.00% | 99.41% | 0.00% | - | - | 0.503280 | 13.501913 | -0.332286 | 10.976187 | -0.009379 | 9.491582 | 4.524127 | 1.427616 | 0.6242 | 0.0705 | 0.4995 | nan | nan |
| 2459993 | RF_maintenance | 100.00% | 0.00% | 97.84% | 0.00% | - | - | 0.543812 | 12.561897 | -0.564746 | 10.179402 | -0.335177 | 10.868383 | 5.818607 | 2.847787 | 0.6180 | 0.0542 | 0.4952 | nan | nan |
| 2459991 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.692681 | 15.728322 | -0.424354 | 10.773292 | -0.291029 | 10.712398 | 7.663793 | 1.936352 | 0.6234 | 0.0636 | 0.5063 | nan | nan |
| 2459990 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.520109 | 12.938796 | -0.391536 | 10.467070 | -0.104679 | 11.010144 | 7.949159 | 2.230517 | 0.6263 | 0.0676 | 0.5042 | nan | nan |
| 2459989 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 0.143310 | 13.117890 | -0.364319 | 9.569774 | -0.173560 | 9.247824 | 7.518146 | 1.789419 | 0.6233 | 0.0634 | 0.5057 | nan | nan |
| 2459988 | RF_maintenance | 100.00% | 0.00% | 99.41% | 0.00% | - | - | 0.275112 | 15.374172 | -0.497826 | 10.760319 | -0.055339 | 13.163383 | 7.620308 | 1.560087 | 0.6199 | 0.0639 | 0.5078 | nan | nan |
| 2459987 | RF_maintenance | 100.00% | 0.00% | 98.00% | 0.00% | - | - | 0.060122 | 12.875711 | -0.466460 | 10.613143 | -0.013115 | 7.928339 | 6.699752 | 3.585369 | 0.6300 | 0.0765 | 0.5047 | nan | nan |
| 2459986 | RF_maintenance | 100.00% | 0.00% | 97.25% | 0.00% | - | - | 0.135703 | 15.829878 | -1.158845 | 11.454359 | -0.459648 | 11.209828 | 0.715719 | 10.775062 | 0.6391 | 0.0872 | 0.4995 | nan | nan |
| 2459985 | RF_maintenance | 100.00% | 0.00% | 99.95% | 0.00% | - | - | 0.192332 | 14.258961 | -1.020288 | 10.669923 | -0.511938 | 8.558881 | 0.268695 | 3.495947 | 0.6190 | 0.0680 | 0.5026 | nan | nan |
| 2459984 | RF_maintenance | 100.00% | 0.00% | 96.54% | 0.00% | - | - | -0.039342 | 13.696569 | -1.050339 | 11.049341 | 0.261141 | 12.128400 | 1.285173 | 5.192158 | 0.6422 | 0.0944 | 0.5036 | nan | nan |
| 2459983 | RF_maintenance | 100.00% | 0.00% | 89.41% | 0.00% | - | - | 1.403565 | 13.432830 | -0.297166 | 10.469464 | -0.096614 | 11.152064 | 1.881101 | 8.250383 | 0.6495 | 0.1010 | 0.4964 | nan | nan |
| 2459982 | RF_maintenance | 100.00% | 0.00% | 85.90% | 0.00% | - | - | 1.572216 | 11.248572 | 0.018489 | 8.916258 | 0.314045 | 5.291593 | 0.416139 | 3.449523 | 0.7006 | 0.1199 | 0.5217 | nan | nan |
| 2459981 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 1.952794 | 12.367424 | -0.438756 | 11.140352 | -0.470748 | 12.311863 | 0.522489 | 2.133850 | 0.6194 | 0.0668 | 0.4992 | nan | nan |
| 2459980 | RF_maintenance | 100.00% | 0.00% | 91.41% | 0.00% | - | - | 1.557268 | 11.895016 | -0.492927 | 10.178975 | -0.251496 | 10.761515 | -0.054962 | 5.417803 | 0.6683 | 0.0978 | 0.5047 | nan | nan |
| 2459979 | RF_maintenance | 100.00% | 0.00% | 99.89% | 0.00% | - | - | 2.090236 | 12.446188 | -0.575956 | 9.527936 | -0.294312 | 10.076490 | 1.396286 | 2.841625 | 0.6092 | 0.0611 | 0.4980 | nan | nan |
| 2459978 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 2.057812 | 12.657621 | -0.574548 | 10.256123 | -0.291598 | 10.941760 | 1.394290 | 2.726160 | 0.6082 | 0.0593 | 0.4991 | nan | nan |
| 2459977 | RF_maintenance | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 1.980715 | 13.365333 | -0.493296 | 10.103604 | 0.193763 | 11.383623 | 2.775015 | 4.444600 | 0.5813 | 0.0688 | 0.4649 | nan | nan |
| 2459976 | RF_maintenance | 100.00% | 0.00% | 99.89% | 0.00% | - | - | 2.160489 | 12.858088 | -0.492656 | 10.527886 | -0.523084 | 10.816517 | 0.543122 | 2.223503 | 0.6242 | 0.0632 | 0.5071 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 14.784285 | 14.784285 | 0.714381 | 11.637773 | -0.066192 | 6.951723 | 0.357222 | 3.193599 | 1.295929 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.406899 | 1.011973 | 12.406899 | -0.218761 | 8.779668 | 0.087114 | 10.444884 | 1.327943 | 2.633047 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 14.804989 | 0.594073 | 14.804989 | -0.088219 | 11.618918 | 0.510901 | 6.975462 | 1.210040 | 3.717934 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.894298 | 0.407701 | 13.894298 | -0.242154 | 11.400661 | 0.754426 | 7.709722 | 4.307500 | 7.484120 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | ee Temporal Variability | 19.488829 | 0.517455 | 14.891704 | -0.334255 | 15.257099 | 19.488829 | 15.857849 | 4.250996 | 3.397269 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 16.295916 | 0.986951 | 16.295916 | -0.519363 | 12.636289 | 0.053648 | 10.391835 | 0.858339 | 2.982025 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 15.015085 | 0.626717 | 15.015085 | -0.302631 | 13.908379 | 0.095143 | 8.777299 | 0.707976 | 3.292995 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 18.488821 | 18.488821 | 0.014746 | 15.312180 | -1.203527 | 7.715746 | 2.564931 | 5.621983 | 0.893621 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.817860 | 0.406703 | 13.817860 | -0.235116 | 11.975844 | 0.258377 | 7.168053 | 6.577181 | 3.394598 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | ee Temporal Discontinuties | 12.009825 | 0.265232 | 11.648321 | -0.226664 | 10.136932 | 0.518058 | 10.162864 | 12.009825 | 3.230424 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | ee Temporal Discontinuties | 14.120246 | 0.294429 | 12.729802 | -0.284608 | 10.892749 | 0.241427 | 9.567914 | 14.120246 | 4.340825 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.701306 | 0.586292 | 13.701306 | 0.067738 | 13.329098 | 0.471000 | 9.207881 | 4.682389 | 1.908670 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.909784 | 0.470560 | 13.909784 | -0.420472 | 12.528205 | -0.002282 | 9.406282 | 5.557310 | 1.735604 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.501913 | 0.503280 | 13.501913 | -0.332286 | 10.976187 | -0.009379 | 9.491582 | 4.524127 | 1.427616 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.561897 | 0.543812 | 12.561897 | -0.564746 | 10.179402 | -0.335177 | 10.868383 | 5.818607 | 2.847787 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 15.728322 | 0.692681 | 15.728322 | -0.424354 | 10.773292 | -0.291029 | 10.712398 | 7.663793 | 1.936352 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.938796 | 12.938796 | 0.520109 | 10.467070 | -0.391536 | 11.010144 | -0.104679 | 2.230517 | 7.949159 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.117890 | 13.117890 | 0.143310 | 9.569774 | -0.364319 | 9.247824 | -0.173560 | 1.789419 | 7.518146 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 15.374172 | 15.374172 | 0.275112 | 10.760319 | -0.497826 | 13.163383 | -0.055339 | 1.560087 | 7.620308 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.875711 | 0.060122 | 12.875711 | -0.466460 | 10.613143 | -0.013115 | 7.928339 | 6.699752 | 3.585369 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 15.829878 | 15.829878 | 0.135703 | 11.454359 | -1.158845 | 11.209828 | -0.459648 | 10.775062 | 0.715719 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 14.258961 | 14.258961 | 0.192332 | 10.669923 | -1.020288 | 8.558881 | -0.511938 | 3.495947 | 0.268695 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.696569 | -0.039342 | 13.696569 | -1.050339 | 11.049341 | 0.261141 | 12.128400 | 1.285173 | 5.192158 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.432830 | 1.403565 | 13.432830 | -0.297166 | 10.469464 | -0.096614 | 11.152064 | 1.881101 | 8.250383 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 11.248572 | 1.572216 | 11.248572 | 0.018489 | 8.916258 | 0.314045 | 5.291593 | 0.416139 | 3.449523 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.367424 | 12.367424 | 1.952794 | 11.140352 | -0.438756 | 12.311863 | -0.470748 | 2.133850 | 0.522489 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 11.895016 | 11.895016 | 1.557268 | 10.178975 | -0.492927 | 10.761515 | -0.251496 | 5.417803 | -0.054962 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.446188 | 2.090236 | 12.446188 | -0.575956 | 9.527936 | -0.294312 | 10.076490 | 1.396286 | 2.841625 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.657621 | 12.657621 | 2.057812 | 10.256123 | -0.574548 | 10.941760 | -0.291598 | 2.726160 | 1.394290 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 13.365333 | 1.980715 | 13.365333 | -0.493296 | 10.103604 | 0.193763 | 11.383623 | 2.775015 | 4.444600 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 60 | N05 | RF_maintenance | nn Shape | 12.858088 | 12.858088 | 2.160489 | 10.527886 | -0.492656 | 10.816517 | -0.523084 | 2.223503 | 0.543122 |